Alharbi Sarah A H, Button Katherine, Zhang Lingshan, O'Shea Kieran J, Fasolt Vanessa, Lee Anthony J, DeBruine Lisa M, Jones Benedict C
Institute of Neuroscience & Psychology, University of Glasgow, Scotland, UK.
Department of Psychology, Taibah University, Medina, Saudi Arabia.
R Soc Open Sci. 2020 Sep 9;7(9):190699. doi: 10.1098/rsos.190699. eCollection 2020 Sep.
Evidence that affective factors (e.g. anxiety, depression, affect) are significantly related to individual differences in emotion recognition is mixed. Palermo . (Palermo . 2018 , 503-517) reported that individuals who scored lower in anxiety performed significantly better on two measures of facial-expression recognition (emotion-matching and emotion-labelling tasks), but not a third measure (the multimodal emotion recognition test). By contrast, facial-expression recognition was not significantly correlated with measures of depression, positive or negative affect, empathy, or autistic-like traits. Because the range of affective factors considered in this study and its use of multiple expression-recognition tasks mean that it is a relatively comprehensive investigation of the role of affective factors in facial expression recognition, we carried out a direct replication. In common with Palermo . (Palermo . 2018 , 503-517), scores on the DASS anxiety subscale negatively predicted performance on the emotion recognition tasks across multiple analyses, although these correlations were only consistently significant for performance on the emotion-labelling task. However, and by contrast with Palermo . (Palermo . 2018 , 503-517), other affective factors (e.g. those related to empathy) often also significantly predicted emotion-recognition performance. Collectively, these results support the proposal that affective factors predict individual differences in emotion recognition, but that these correlations are not necessarily specific to measures of general anxiety, such as the DASS anxiety subscale.
情感因素(如焦虑、抑郁、情感)与情绪识别中的个体差异显著相关的证据并不一致。巴勒莫(Palermo,2018年,第503 - 517页)报告称,焦虑得分较低的个体在两项面部表情识别测试(情绪匹配和情绪标记任务)中表现明显更好,但在第三项测试(多模态情绪识别测试)中并非如此。相比之下,面部表情识别与抑郁、积极或消极情感、同理心或自闭症样特征的测量指标没有显著相关性。由于本研究中考虑的情感因素范围及其对多种表情识别任务的使用意味着它是对情感因素在面部表情识别中作用的相对全面的调查,我们进行了直接复制。与巴勒莫(Palermo,2018年,第503 - 517页)的研究相同,在多项分析中,抑郁焦虑量表(DASS)焦虑子量表的得分对情绪识别任务的表现有负向预测作用,尽管这些相关性仅在情绪标记任务的表现上始终显著。然而,与巴勒莫(Palermo,2018年,第503 - 517页)的研究不同,其他情感因素(如与同理心相关的因素)通常也能显著预测情绪识别表现。总体而言,这些结果支持了情感因素能预测情绪识别中的个体差异这一观点,但这些相关性不一定特定于一般焦虑的测量指标,如DASS焦虑子量表。